Model Evaluation Metrics

from sklearn.metrics import (
    accuracy_score, precision_score, recall_score, 
    f1_score, confusion_matrix, classification_report
)
 
# All metrics at once
print(classification_report(y_true, y_pred))
 
# Individual metrics
accuracy = accuracy_score(y_true, y_pred)
precision = precision_score(y_true, y_pred, average='weighted')
recall = recall_score(y_true, y_pred, average='weighted')
f1 = f1_score(y_true, y_pred, average='weighted')
 
# Confusion matrix
cm = confusion_matrix(y_true, y_pred)